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Spice v0.13.2-alpha (June 3, 2024)

· 4 min read
Luke Kim
Luke Kim
Founder and CEO of Spice AI

The v0.13.2-alpha release is focused on quality and stability with improvements to federated query push-down, telemetry, and query history.

Highlights​

  • Filesystem Data Connector: Adds the Filesystem Data Connector for directly using files as data sources.

  • Federated Query Push-Down: Improved stability and schema compatibility for federated queries.

  • Enhanced Telemetry: Runtime Metrics now include last update time for accelerated datasets, count of refresh errors, and new metrics for query duration and failures.

  • Query History: Enabled query history logging for Arrow Flight queries in addition to HTTP queries.

Spice v0.13.1-alpha (May 27, 2024)

· 5 min read
Luke Kim
Luke Kim
Founder and CEO of Spice AI

The v0.13.1-alpha release of Spice is a minor update focused on stability, quality, and operability. Query result caching provides protection against bursts of queries and schema support for datasets has been added logical grouping. An issue where Refresh SQL predicates were not pushed down underlying data sources has been resolved along with improved Acceleration Refresh logging.

Highlights in v0.13.1-alpha​

  • Results Caching: Introduced query results caching to handle bursts of requests and support caching of non-accelerated results, such as refresh data returned on zero results. Results caching is enabled by default with a 1s item time-to-live (TTL). Learn more.

  • Query History Logging: Recent queries are now logged in the new spice.runtime.query_history dataset with a default retention of 24-hours. Query history is initially enabled for HTTP queries only (not Arrow Flight queries).

  • Dataset Schemas: Added support for dataset schemas, allowing logical grouping of datasets by separating the schema name from the table name with a .. E.g.

    datasets:
      - from: mysql:app1.identities
        name: app.users

      - from: postgres:app2.purchases
        name: app.purchases

    In this example, queries against app.users will be federated to my_schema.my_table, and app.purchases will be federated to app2.purchases.